在癌症患者中,患者报告的结果-衍生症状复杂性和整体存活率之间的关联
Linda Watson1,2, Claire Link1, Siwei Qi1
11Cancer Care Alberta, Calgary, Alberta, Canada.
Journal of the National Comprehensive Cancer Network : JNCCN
|February 16, 2026
概括
在癌症患者中,较高的症状复杂性与较短的整体存活期 (OS) 有关. 这种患者报告结果 (PROs) 算法可以帮助预测存活率并指导临床决策.
科学领域:
- 在瘤学瘤学.
- 患者报告的结果
- 预测生物标志物 预测生物标志物
背景情况:
- 阿尔伯塔癌症护理局 (CCA) 开发了一种患者报告结果 (PRO) 衍生算法,以得分症状复杂性.
- 该算法将患者分为低,中等或高症状复杂性的组.
- 研究了这个算法对整体存活 (OS) 的预后效用.
研究的目的:
- 检查癌症患者的症状复杂性得分和整体存活期 (OS) 之间的关联.
- 为了确定CCA症状复杂性算法的预后值.
主要方法:
- 包括5,841名在2019年10月至2020年4月期间进行初始瘤咨询的成年患者.
- 在咨询后30天内,使用PRO问卷评估症状复杂性.
- 分析了使用卡普兰-梅尔曲线和考克斯比例危险模型的操作系统,并对共变量进行调整.
主要成果:
- 较高的基线症状复杂性与较短的生存期相关 (低:64.7周,中度:39.0周,高:25.7周).
- 与低复杂度相比,中度复杂度患者死亡风险增加了69% (HR 1.69),高复杂度患者死亡风险增加了142% (HR 2.42).
- 人口和临床变量在复杂程度上有所不同.
结论:
- 增加的症状复杂性,根据CCA算法测量,是较短的OS的显著预测因素.
- 来自PRO的症状复杂度得分在预测癌症患者存活率方面具有实用性.
- 结果可以为治疗计划和支持性护理的临床决策提供信息.
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